This paper describes a distributed modeling approach applied to modeling
stream flow in the 3817 km2 Grey River in New Zealand. We have assembled
and used a modeling system centered on TOPMODEL, for the simulation of
saturation excess runoff based upon topography, but included other components
to represent all the hydrologic processes deemed relevant. Precipitation
was spatially interpolated from twenty five rain gauges using linear interpolation
on Delauney triangles and scaling by an annual rainfall surface to represent
orographic effects. The model included components for estimating
reference evapotranspiration from temperature, modeling interception and
throughfall, an unsaturated zone soil layer that delayed water inputs to
the saturated zone and provided infiltration excess runoff generation capability,
and a kinematic wave channel routing component. Procedures were developed
to generate model input files from digital elevation model and land resource
inventory Geographic Information System (GIS) data. Model elements
are subwatersheds automatically extracted based upon the channel network
extracted from the digital elevation model and a specified stream order
threshold. Model element parameters are linked to GIS information
averaged over each subwatershed. We were able to handle subdivision
into up to 200 subwatersheds. The model was calibrated using an interactive
calibration package utilizing the Gauss-Marquardt method. The calibration
uses scale multipliers to retain GIS landcover derived relative differences
between parameters across subwatersheds. Model parameters were first
calibrated against a small subwatershed for one year then independently
tested there for a later year. The calibration used precipitation measured
at this small watershed while the validation exercised the precipitation
interpolation methodology. The model was then applied to the whole
Grey basin, with the same parameters and compared to flow measured at the
basin outlet, and eight other water level recorders in the basin. Our results
indicate that streamflow estimates are sensitive to uncertainty in the
precipitation due to variability and orographic effects and that this precipitation
uncertainty dominates over uncertainty in other basin characteristics.
We discuss efforts to reconcile the spatial pattern of rainfall with rain
gage and stream flow measurements across this watershed.